http://www.cnr.it/ontology/cnr/individuo/prodotto/ID235150
XML class outlier detection (Contributo in atti di convegno)
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- XML class outlier detection (Contributo in atti di convegno) (literal)
- Anno
- 2012-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1145/2351476.2351494 (literal)
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Giuseppe Manco, Elio Masciari (2012)
XML class outlier detection
in 16th International Database Engineering and Applications Symposium, IDEAS 2012, Prague; Czech Republic, 8 August 2012 through 10 August 2012
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Giuseppe Manco, Elio Masciari (literal)
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of the 16th International Database Engineering & Applications Sysmposium (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Titolo
- XML class outlier detection (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- 978-1-4503-1234-9 (literal)
- Abstract
- XML (eXtensible Markup Language) became in recent years the new standard for data representation and exchange on the WWW. This has resulted in a great need for data cleaning techniques in order to identify outlying data. In this paper, we present a technique for outlier detection that singles out anomalies with respect to a relevant group of objects. We exploit a suitable encoding of XML documents that are encoded as signals of fixed frequency that can be transformed using Fourier Transforms. Outliers are identified by simply looking at the signal spectra. The results show the effectiveness of our approach. (literal)
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